首页> 外国专利> A method for on-device learning of a machine learning network of an autonomous vehicle through multi-stage learning using an adaptive hyperparameter set, and an on-device learning device using the same

A method for on-device learning of a machine learning network of an autonomous vehicle through multi-stage learning using an adaptive hyperparameter set, and an on-device learning device using the same

机译:一种通过使用自适应超参数集的多阶段学习的自主车辆机器学习网络的设备学习方法,以及使用相同的On-Device学习设备

摘要

The present invention relates to a method for on-device learning of a machine learning network through multi-stage learning using adaptive hyperparameters. Classifying into n-th stage learning, generating first-stage learning data to n-th stage learning data, generating a first hyperparameter set candidate to hyperparameter set candidate based on default values of each of the hyperparameters, and the machine learning training a network, selecting the machine learning network with the highest performance, and generating a first adaptive hyperparameter set; (b) (k_1)th hyperparameter set candidates to (k_h)th hyperparameter set candidates are generated, trained using the kth stage training data, and the (k-1)th stage trained machine with the highest performance selecting a learning network and generating a k-th adaptive hyperparameter set; and (c) generating an n-th adaptive hyperparameter set and completing the current learning by performing n-th stage learning. A method and an apparatus using the same are disclosed.
机译:本发明涉及一种通过使用自适应超参数来通过多阶段学习来学习机器学习网络的设备学习方法。将第一阶段学习数据分类为第n阶段学习数据,基于每个超参数的默认值和机器学习训练网络的默认值生成第一阶段学习数据,生成第一阶段学习数据。选择具有最高性能的机器学习网络,并生成第一自适应覆盖物集; (b)(k_1)Th HyperParameter将候选者设置为(k_h)Th HyperParameter设置候选者,使用Kth阶段训练数据进行培训,以及(K-1)TH级训练机,具有最高性能选择学习网络和生成一个k-th自适应覆盖物集; (c)通过执行第n阶段学习来生成第n个自适应封路数据设置并完成当前学习。公开了一种方法和使用该方法的装置。

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